Model Card
This model is designed to provide enhanced performance over the base LLaMA 2 Chat 7B model by incorporating more recent data and domain-specific knowledge. The fine-tuning process aimed to improve the model's accuracy, conversational abilities, and understanding of up-to-date information across a range of topics.
Model Description
The model was fine-tuned on a curated dataset composed of the following sources:
Updated Information Dataset: A collection of recent articles, news updates, and relevant literature ensuring the model has access to current information. Domain-Specific Datasets: Specialized datasets in areas such as technology, medicine, and climate change, aiming to enhance the model's expertise in these fields. Conversational Interactions: A dataset derived from anonymized conversational exchanges, improving the model's natural language understanding and generation in chat-like scenarios.
- Developed by: Aneeb Ajmal
- Language(s) (NLP): English
- License: Apache 2.0
- Finetuned from model: LLaMA (Large Language Model Meta AI) 2 Chat 7B
Training
- Fine-Tuning Period: 1 hour
- Optimizer: paged_adamw_32bit
- Learning Rate: 2e-4
- Training Infrastructure: Google Colab T4 GPU
- Evaluation Metrics: Accuracy, Perplexity, F1 Score, and Domain-Specific Benchmarks
Ethical Considerations
During the development and fine-tuning of this model, considerations were made regarding:
- Data Bias and Fairness: Efforts to mitigate biases in the training data and ensure fair representation across demographics.
- Privacy: Measures taken to anonymize and protect sensitive information in the training data.
- Use Case Restrictions: Guidelines on responsible usage, highlighting areas where the model's predictions should be used with caution.
Intended Use
This model is intended for use in applications requiring enhanced conversational abilities, up-to-date information, and domain-specific knowledge, including but not limited to chatbots, virtual assistants, and information retrieval systems. It is not designed for scenarios requiring absolute accuracy, such as medical diagnosis or legal advice.
Limitations
The model may still exhibit biases or inaccuracies in certain contexts, despite efforts to mitigate these issues during fine-tuning. The effectiveness of the model can vary significantly depending on the domain and specificity of the queries.
How to Use
You can access this model by using the transformers library directly.
Contact
For questions, feedback, or support regarding the fine-tuned LLaMA 2 Chat 7B model, please contact [email protected].
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